A New Tubular Structure Tracking Algorithm Based On Curvature-Penalized Perceptual Grouping

Liu, Li; Chen, Da; Shu, Ming-Lei; Shu, Huazhong; Cohen, Laurent D.

Liu, Li; Chen, Da; Shu, Ming-Lei; Shu, Huazhong; Cohen, Laurent D. (2021), A New Tubular Structure Tracking Algorithm Based On Curvature-Penalized Perceptual Grouping, IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2021, IEEE - Institute of Electrical and Electronics Engineers : Piscataway, NJ. 10.1109/icassp39728.2021.9414114

Type

Communication / Conférence

External document link

https://hal.archives-ouvertes.fr/hal-03424096

Date

2021

Conference title

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Conference date

2021-06

Conference city

Piscataway, NJ

Conference country

United States

Book title

IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2021

Publisher

IEEE - Institute of Electrical and Electronics Engineers

Published in

Piscataway, NJ

Donghua University [Shanghai]
Chen, Da
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Shandong Artificial Intelligence Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
Shu, Ming-Lei
Shandong Artificial Intelligence Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
Shu, Huazhong
Laboratory of Image Science and Technology [Nanjing] [LIST]
Cohen, Laurent D.
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]

Abstract (EN)

In this paper, we propose a new minimal path-based framework for minimally interactive tubular structure tracking in conjunction with a perceptual grouping scheme. The minimal path models have shown great advantages in tubular structures tracing. However, they suffer from shortcuts or short branches combination problems especially in the case of tubular network with complicated structures or background. Thus, we utilize the curvature-penalized minimal paths and the prescribed tubular trajectories to seek the desired shortest path. The proposed approach benefits from the local smoothness prior on tubular structures and the global optimality of the graph-based path searching scheme. Experimental results on synthetic and real images prove that the proposed model indeed obtains outperformance to state-of-the-art minimal path-based algorithms.

Subjects / Keywords

Tubular structure tracking; minimal path; perceptual grouping; curvature regularization